Publications Details

Publication Details

Explanation as a Social Practice

Toward a Conceptual Framework for the Social Design of AI Systems

authored by
Katharina J. Rohlfing, Philipp Cimiano, Ingrid Scharlau, Tobias Matzner, Heike M. Buhl, Hendrik Buschmeier, Elena Esposito, Angela Grimminger, Barbara Hammer, Reinhold Hab-Umbach, Ilona Horwath, Eyke Hullermeier, Friederike Kern, Stefan Kopp, Kirsten Thommes, Axel Cyrille Ngonga Ngomo, Carsten Schulte, Henning Wachsmuth, Petra Wagner, Britta Wrede

The recent surge of interest in explainability in artificial intelligence (XAI) is propelled by not only technological advancements in machine learning but also by regulatory initiatives to foster transparency in algorithmic decision making. In this article, we revise the current concept of explainability and identify three limitations: passive explainee, narrow view on the social process, and undifferentiated assessment of explainee's understanding. In order to overcome these limitations, we present explanation as a social practice in which explainer and explainee co-construct understanding on the microlevel. We view the co-construction on a microlevel as embedded into a macrolevel, yielding expectations concerning, e.g., social roles or partner models: typically, the role of the explainer is to provide an explanation and to adapt it to the current level of explainee's understanding; the explainee, in turn, is expected to provide cues that direct the explainer. Building on explanations being a social practice, we present a conceptual framework that aims to guide future research in XAI. The framework relies on the key concepts of monitoring and scaffolding to capture the development of interaction. We relate our conceptual framework and our new perspective on explaining to transparency and autonomy as objectives considered for XAI.

External Organisation(s)
Paderborn University
Bielefeld University
IEEE Transactions on Cognitive and Developmental Systems
No. of pages
Publication date
Publication status
Peer reviewed
ASJC Scopus subject areas
Software, Artificial Intelligence
Electronic version(s) (Access: Open)